Channel Estimation for RIS-aided mmWave Communications via 3D Positioning

Abstract

Millimeter-wave (mmWave) communication is one of the key technologies for the fifth-generation cellular networks (5G). However, one of the fundamental problems of mmWave communication is the susceptibility to blockage effects. One way to alleviate this effect is the use of Reconfigurable Intelligent Surface (RIS). Nevertheless, due to the large number of passive reflecting elements on RIS, the channel estimation turns out to be a challenging task. This paper proposes a novel 3D localization technology to achieve the low-complexity channel estimation for RIS-aided mmWave communication system. Our idea consists of exploiting the sparsity of the mmWave channel and the topology of RIS itself. In particular, we propose the concept of reflecting unit set (RUS) and a coplanar maximum likelihood-based (CML) efficient 3D positioning method, and derive the corresponding Cramer-Rao Lower Bounds (CRLB) in close-form. Compared to state-of-the-art methods, our proposed method requires less time-frequency resource in channel acquisition. Large performance gains are confirmed in simulation, which proves the effectiveness of our proposed method.